2017
Contribution to book  Open Access

Intermittency-driven complexity in signal processing

Paradisi P., Allegrini P.

Heart  Brain  ElectroCardioGram (ECG)  ElectroEncephaloGram (EEG)  Fractal Intermittency  Health and wellness  Physiology  Biomedical signal processing 

In this chapter, we rst discuss the main motivations that are causing an increasing interest of many research elds and the interdisciplinary eort of many research groups towards the new paradigm of complexity. Then, without claiming to include all possible complex systems, which is much beyond the cope of this review, we introduce a possible denition of complexity. Along this line, we also introduce our particular approach to the analysis and modeling of complex systems. This is based on the ubiquitous observation of metastability of self-organization, which triggers the emergence of intermittent events with fractal statistics. This condition, named fractal intermittency, is the signature of a particular class of complexity here referred to as Intermittency-Driven Complexity (IDC) . Limiting to the IDC framework, we give a survey of some recently developed statistical tools for the analysis of complex behavior in multi-component systems and we review recent applications to real data, especially in the eld of human physiology. Finally, we give a brief discussion about the role of complexity paradigm in human health and wellness.

Source: Complexity and Nonlinearity in Cardiovascular Signals, edited by Barbieri R.; Scilingo E.; Valenza G., pp. 161–195. London: Springer, 2017

Publisher: Springer, London, GBR


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BibTeX entry
@inbook{oai:it.cnr:prodotti:401216,
	title = {Intermittency-driven complexity in signal processing},
	author = {Paradisi P. and Allegrini P.},
	publisher = {Springer, London, GBR},
	doi = {10.1007/978-3-319-58709-7_6},
	booktitle = {Complexity and Nonlinearity in Cardiovascular Signals, edited by Barbieri R.; Scilingo E.; Valenza G., pp. 161–195. London: Springer, 2017},
	year = {2017}
}